Benchmark refactoring

examples/build.gradle.kts

@@ -69,7 +69,7 @@ benchmark {
     // This one matches sourceSet name above
 
     configurations.register("fast") {
-        warmups = 5 // number of warmup iterations
+        warmups = 1 // number of warmup iterations
         iterations = 3 // number of iterations
         iterationTime = 500 // time in seconds per iteration
         iterationTimeUnit = "ms" // time unity for iterationTime, default is seconds

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ArrayBenchmark.kt

@@ -1,4 +1,4 @@
-package kscience.kmath.structures
+package kscience.kmath.benchmarks
 
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/BufferBenchmark.kt

@@ -1,7 +1,9 @@
-package kscience.kmath.structures
+package kscience.kmath.benchmarks
 
 import kscience.kmath.operations.Complex
 import kscience.kmath.operations.complex
+import kscience.kmath.structures.MutableBuffer
+import kscience.kmath.structures.RealBuffer
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/LinearAlgebraBenchmark.kt

@@ -0,0 +1,50 @@
+package kscience.kmath.linear
+
+
+import kotlinx.benchmark.Benchmark
+import kscience.kmath.commons.linear.CMMatrixContext
+import kscience.kmath.commons.linear.CMMatrixContext.dot
+import kscience.kmath.commons.linear.inverse
+import kscience.kmath.commons.linear.toCM
+import kscience.kmath.ejml.EjmlMatrixContext
+import kscience.kmath.ejml.inverse
+import kscience.kmath.ejml.toEjml
+import kscience.kmath.operations.invoke
+import kscience.kmath.structures.Matrix
+import org.openjdk.jmh.annotations.Scope
+import org.openjdk.jmh.annotations.State
+import kotlin.random.Random
+
+@State(Scope.Benchmark)
+class LinearAlgebraBenchmark {
+    companion object {
+        val random = Random(1224)
+        val dim = 100
+
+        //creating invertible matrix
+        val u = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
+        val l = Matrix.real(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
+        val matrix = l dot u
+    }
+
+    @Benchmark
+    fun kmathLUPInversion() {
+        MatrixContext.real.inverse(matrix)
+    }
+
+    @Benchmark
+    fun cmLUPInversion() {
+        CMMatrixContext {
+            val cm = matrix.toCM()             //avoid overhead on conversion
+            inverse(cm)
+        }
+    }
+
+    @Benchmark
+    fun ejmlInverse() {
+        EjmlMatrixContext {
+            val km = matrix.toEjml()      //avoid overhead on conversion
+            inverse(km)
+        }
+    }
+}

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/MultiplicationBenchmark.kt

@@ -1,4 +1,4 @@
-package kscience.kmath.structures
+package kscience.kmath.benchmarks
 
 import kotlinx.benchmark.Benchmark
 import kscience.kmath.commons.linear.CMMatrixContext
@@ -7,8 +7,8 @@ import kscience.kmath.commons.linear.toCM
 import kscience.kmath.ejml.EjmlMatrixContext
 import kscience.kmath.ejml.toEjml
 import kscience.kmath.linear.real
-import kscience.kmath.operations.RealField
 import kscience.kmath.operations.invoke
+import kscience.kmath.structures.Matrix
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State
 import kotlin.random.Random
@@ -44,6 +44,15 @@ class MultiplicationBenchmark {
         }
     }
 
+    @Benchmark
+    fun ejmlMultiplicationwithConversion() {
+        val ejmlMatrix1 = matrix1.toEjml()
+        val ejmlMatrix2 = matrix2.toEjml()
+        EjmlMatrixContext.invoke {
+            ejmlMatrix1 dot ejmlMatrix2
+        }
+    }
+
     @Benchmark
     fun bufferedMultiplication() {
         matrix1 dot matrix2

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/NDFieldBenchmark.kt

@@ -1,7 +1,8 @@
-package kscience.kmath.structures
+package kscience.kmath.benchmarks
 
 import kscience.kmath.operations.RealField
 import kscience.kmath.operations.invoke
+import kscience.kmath.structures.*
 import org.openjdk.jmh.annotations.Benchmark
 import org.openjdk.jmh.annotations.Scope
 import org.openjdk.jmh.annotations.State

examples/src/benchmarks/kotlin/kscience/kmath/benchmarks/ViktorBenchmark.kt

@@ -1,7 +1,10 @@
-package kscience.kmath.structures
+package kscience.kmath.benchmarks
 
 import kscience.kmath.operations.RealField
 import kscience.kmath.operations.invoke
+import kscience.kmath.structures.BufferedNDField
+import kscience.kmath.structures.NDField
+import kscience.kmath.structures.RealNDField
 import kscience.kmath.viktor.ViktorNDField
 import org.jetbrains.bio.viktor.F64Array
 import org.openjdk.jmh.annotations.Benchmark
@@ -36,7 +39,7 @@ internal class ViktorBenchmark {
 
     @Benchmark
     fun rawViktor() {
-        val one = F64Array.full(init = 1.0, shape = *intArrayOf(dim, dim))
+        val one = F64Array.full(init = 1.0, shape = intArrayOf(dim, dim))
         var res = one
         repeat(n) { res = res + one }
     }

examples/src/benchmarks/kotlin/kscience/kmath/utils/utils.kt

@@ -1,11 +0,0 @@
-package kscience.kmath.utils
-
-import kotlin.contracts.InvocationKind
-import kotlin.contracts.contract
-import kotlin.system.measureTimeMillis
-
-internal inline fun measureAndPrint(title: String, block: () -> Unit) {
-    contract { callsInPlace(block, InvocationKind.EXACTLY_ONCE) }
-    val time = measureTimeMillis(block)
-    println("$title completed in $time millis")
-}

examples/src/main/kotlin/kscience/kmath/linear/LinearAlgebraBenchmark.kt

@@ -1,52 +0,0 @@
-package kscience.kmath.linear
-
-import kscience.kmath.commons.linear.CMMatrixContext
-import kscience.kmath.commons.linear.CMMatrixContext.dot
-import kscience.kmath.commons.linear.inverse
-import kscience.kmath.commons.linear.toCM
-import kscience.kmath.ejml.EjmlMatrixContext
-import kscience.kmath.ejml.inverse
-import kscience.kmath.ejml.toEjml
-import kscience.kmath.operations.RealField
-import kscience.kmath.operations.invoke
-import kscience.kmath.structures.Matrix
-import kotlin.random.Random
-import kotlin.system.measureTimeMillis
-
-fun main() {
-    val random = Random(1224)
-    val dim = 100
-    //creating invertible matrix
-    val u = Matrix.real(dim, dim) { i, j -> if (i <= j) random.nextDouble() else 0.0 }
-    val l = Matrix.real(dim, dim) { i, j -> if (i >= j) random.nextDouble() else 0.0 }
-    val matrix = l dot u
-
-    val n = 5000 // iterations
-
-    MatrixContext.real {
-        repeat(50) { inverse(matrix) }
-        val inverseTime = measureTimeMillis { repeat(n) { inverse(matrix) } }
-        println("[kmath] Inversion of $n matrices $dim x $dim finished in $inverseTime millis")
-    }
-
-    //commons-math
-
-    val commonsTime = measureTimeMillis {
-        CMMatrixContext {
-            val cm = matrix.toCM()             //avoid overhead on conversion
-            repeat(n) { inverse(cm) }
-        }
-    }
-
-
-    println("[commons-math] Inversion of $n matrices $dim x $dim finished in $commonsTime millis")
-
-    val ejmlTime = measureTimeMillis {
-        EjmlMatrixContext {
-            val km = matrix.toEjml()      //avoid overhead on conversion
-            repeat(n) { inverse(km) }
-        }
-    }
-
-    println("[ejml] Inversion of $n matrices $dim x $dim finished in $ejmlTime millis")
-}

kmath-core/src/commonMain/kotlin/kscience/kmath/linear/FeaturedMatrix.kt

@@ -80,4 +80,4 @@ public fun <T : Any> Matrix<T>.transpose(): Matrix<T> {
         rowNum,
         setOf(TransposedFeature(this))
     ) { i, j -> get(j, i) }
-}
+}